Cloud-Control of Legacy Building Automation System: A case study

Conference · Mon Aug 01 04:00:00 EDT 2022

DOI:https://doi.org/10.20357/B7BS4H· OSTI ID:1887799

Prakash, Anand Krishnan ^[1]; Pritoni, Marco ^[1]; Kloss, Margarita ^[1]; Piette, Mary Ann ^[1]; Kamel, Michel ^[2]; Hage, Dotty ^[2]

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1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
2. MelRok LLC, Santa Ana, CA (United States)

As Internet of Things devices and cloud-based platforms become more mature, Energy Management and Information Systems (EMIS) are increasingly gaining momentum in the building industry. In large commercial buildings, Fault-Detection and Diagnostic (FDD) and energy information systems (EIS) are now established technologies with tens of providers and thousands of deployment sites across North America. The new frontier for the EMIS technology is now represented by control systems that use advanced system optimization (ASO) methods to improve the operations of the HVAC system. Given the complexity of the integration of such systems with the existing building automation systems (BAS) and the higher risk involved with direct control of the HVAC, these systems are still emerging in the market. This paper presents the results of a project in which a start-up company partnered with a research institution to develop a cloud-based software EMIS solution and deployed it in a university campus in California. The software system included advanced sensing, data acquisition, storage and advanced control and analytics applications developed on top of the native BAS. The new platform controls ten buildings on the campus and the FDD and the ASO applications deployed on this platform were able to generate energy savings of up to 35% and 25% in certain buildings for each functionality respectively. Where the platform did not save energy, it improved building service (air quality). Lessons learned include the importance of collaborating with and training the building operators and evaluating whether the legacy system can work reliably with the new technology.

• Research Organization: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Building Technologies Office (EE-5B)
• DOE Contract Number: AC02-05CH11231
• OSTI ID: 1887799
• Country of Publication: United States
• Language: English